Add max nodes limit for graph retrieval of networkX
• Set MAX_GRAPH_NODES env var (default 1000) • Change edge type to "RELATED"
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@@ -3,6 +3,7 @@
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# PORT=9621
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# WORKERS=1
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# NAMESPACE_PREFIX=lightrag # separating data from difference Lightrag instances
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# MAX_GRAPH_NODES=1000 # Max nodes return from grap retrieval
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# CORS_ORIGINS=http://localhost:3000,http://localhost:8080
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### Optional SSL Configuration
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@@ -16,12 +16,27 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
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@router.get("/graph/label/list", dependencies=[Depends(optional_api_key)])
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async def get_graph_labels():
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"""Get all graph labels"""
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"""
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Get all graph labels
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Returns:
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List[str]: List of graph labels
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"""
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return await rag.get_graph_labels()
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@router.get("/graphs", dependencies=[Depends(optional_api_key)])
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async def get_knowledge_graph(label: str, max_depth: int = 3):
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"""Get knowledge graph for a specific label"""
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"""
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Get knowledge graph for a specific label.
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Maximum number of nodes is limited to env MAX_GRAPH_NODES(default: 1000)
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Args:
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label (str): Label to get knowledge graph for
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max_depth (int, optional): Maximum depth of graph. Defaults to 3.
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Returns:
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Dict[str, List[str]]: Knowledge graph for label
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"""
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return await rag.get_knowledge_graph(node_label=label, max_depth=max_depth)
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return router
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@@ -24,6 +24,8 @@ from .shared_storage import (
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is_multiprocess,
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)
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MAX_GRAPH_NODES = int(os.getenv("MAX_GRAPH_NODES", 1000))
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@final
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@dataclass
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@@ -234,6 +236,7 @@ class NetworkXStorage(BaseGraphStorage):
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) -> KnowledgeGraph:
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"""
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Get complete connected subgraph for specified node (including the starting node itself)
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Maximum number of nodes is limited to env MAX_GRAPH_NODES(default: 1000)
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Args:
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node_label: Label of the starting node
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@@ -269,18 +272,17 @@ class NetworkXStorage(BaseGraphStorage):
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subgraph = nx.ego_graph(graph, nodes_to_explore[0], radius=max_depth)
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# Check if number of nodes exceeds max_graph_nodes
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max_graph_nodes = 500
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if len(subgraph.nodes()) > max_graph_nodes:
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if len(subgraph.nodes()) > MAX_GRAPH_NODES:
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origin_nodes = len(subgraph.nodes())
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node_degrees = dict(subgraph.degree())
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top_nodes = sorted(node_degrees.items(), key=lambda x: x[1], reverse=True)[
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:max_graph_nodes
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:MAX_GRAPH_NODES
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]
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top_node_ids = [node[0] for node in top_nodes]
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# Create new subgraph with only top nodes
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# Create new subgraph and keep nodes only with most degree
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subgraph = subgraph.subgraph(top_node_ids)
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logger.info(
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f"Reduced graph from {origin_nodes} nodes to {max_graph_nodes} nodes (depth={max_depth})"
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f"Reduced graph from {origin_nodes} nodes to {MAX_GRAPH_NODES} nodes (depth={max_depth})"
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)
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# Add nodes to result
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@@ -320,7 +322,7 @@ class NetworkXStorage(BaseGraphStorage):
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result.edges.append(
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KnowledgeGraphEdge(
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id=edge_id,
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type="DIRECTED",
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type="RELATED",
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source=str(source),
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target=str(target),
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properties=edge_data,
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